한국지능시스템학회논문지 (Journal of the Korean Institute of Intelligent Systems)

  • 제18권2호
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  • Pages.216-222
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  • 2008
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  • 1976-9172(pISSN)
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  • 2288-2324(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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DOI QR코드

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자연영상에서 컬러분할과 LoG연산특성을 이용한 다중 문자 검출에 관한 연구

Multi Characters Detection Using Color Segmentation and LoG operator characteristics in Natural Scene

  • 신성 (원광대학교 전자공학과) ;
  • 백영현 (원광대학교 전자공학과) ;
  • 문성룡 (원광대학교 전자공학과)
  • 발행 : 2008.04.25
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초록

본 논문은 배경복잡성, 조명변화, 무질서한 라인, 문자와 배경색의 유사성 등에 취약한 기존 연구의 단점을 보완하기 위해 컬러분할과 LoG연산자의 폐곡선 에지 특징 및 합성논리모델을 이용한 다중 문자 검출 알고리즘을 제안하였다. 제안된 다중 문자 검출 알고리즘은 특징 검출, 문자형성, 문자검출 단계로 구성된다. 본 논문에서 제안한 새로운 다중 문자 검출 알고리즘은 웨이브렛, 형태학과 허프변환을 이용한 전처리 후 각 컬러영역을 순차적 AND 연산 및 OR연산을 수행함으로써 완전한 문자가 아닌 불완전 문자부분마저도 취합하여 검출률을 높일 수 있는 효율적인 방법임을 확인하였다. 또한 영상의 크기나 해상도, 기울어짐 등에 상관없이 문자영역이 첨가된 자연 영상을 대상으로 하며, 동일 영상에 대하여 기존의 문자 검출 알고리즘과 비교함으로써 제안알고리즘이 검출률면에서 우수함을 확인하였다.

This paper proposed the multi characters detection algorithm using Color segmentation and the closing curve feature of LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of left and background color, etc. The proposed multi characters detection algorithm divided into three parts : The feature detection, characters format and characters detection Parts in order to be possible to apply to image of various feature. After preprocess that the new multi characters detection algorithm that proposed in this paper used wavelet, morphology, hough transform which is the synthesis logical model in order to raise detection rate by acquiring the non-perfection characters as well as the perfection characters with processing OR operation after processing each color area by AND operation sequentially. And the proposal algorithm is simulated with natural images which include natural character area regardless of size, resolution and slant and so on of image. And the proposal algorithm in this paper is confirmed to an excellent detection rate by compared with the conventional detection algorithm in same image.

키워드

참고문헌

  1. Yu Zhong, Kalle Karu, Anil K. Jain, "Locating Text in Complex Images", Pattern Recognition, Vol. 28, No. 10, pp. 1523-1535, 1995 https://doi.org/10.1016/0031-3203(95)00030-4
  2. Lixu Gu, Toyahisa Kaneko, "Robust extraction of Characters from color scene Image Using Mathematical morphology", Proc. of 7th Int. Conf. on Pattern Recognition, Vol. 2, pp. 1002-1004, 1998
  3. P. K. Kim, "Automatic Text Location in Complex Color Images using Local Color Quantization", TENCON 99. Proc. of the IEEE Region 10 Conference, Vol. 1, pp. 629-632, 1999
  4. K. C. Kim, "Scene Text Extraction in Natural Scene Images using Hierarchical Feature Combining and Verification", Proc. of 17th Int. Conf. on Pattern Recognition, Vol. 4, pp. 1051-4651, 2004
  5. J. S. Kim, "Text Locating from Natural Scene Images Using Image Intensities", Proc. of the 2005 Eight Int. Conf. on Document Analysis and Recognition, Vol. 5, pp. 1520-5263, 2005
  6. R. Crane, "A simplified approach to Image Processing". Prentice-Hall, 1997
  7. C. S. Burrus, and R. A. Gopinath, and H. Guo, "Introduction to Wavelets and Wavelet Transforms", Prentice-Hall, Inc., 1998
  8. Ulupinar, F. and Medioni, G., "Refining edge detected by a LoG operator". IEEE Proc. Computer Vision and Pattern Recognition, pp. 202-207, 1998
  9. D. F. Rogers, "Procedural elements for computer graphics", McGraw-Hill, 1985
  10. R.Gonzalez and R.Woods, "Digital Image Process ing".Addison-Wesley Publishing Company, 1992
  11. Robust Reading Competition Database, Retrived October 20, 2004 from http://algoval.essex.ac.uk/icdar/RobustWord.html
  12. S. M. Lucas, A. Panaretos, L. Sosa, A. Tang, S. Wong and R.Young, "ICDAR 2003 Robust Reading Competition", International Conference on Document Analysis and Recognition(ICDAR), Vol. 2, pp. 682-687, 2003